The invention relates generally to image processing and image analysis. More specifically, the present techniques relate to analysis of tissue microarrays.
Tissue microarray (TMA) technology has become the standard in large-scale immunohistochemistry (IHC), fluorescent in situ hybridization (FISH), and mRNA in situ hybridization (RNA-ISH) studies for protein, DNA and RNA expression. To prepare the TMA slides, a tissue core is typically obtained from the patient tissue and inserted in a paraffin recipient block. The resulting recipient block typically has hundreds of tissue cores from multiple patients. This block may then be cut into sections with many different tissue spots corresponding to the tissue cores. The sections may be placed on glass slides for examination and imaging.
The development of TMA technology has generated interest in studies involving multiple biomarkers that may be performed on a single slide, e.g., sequential tissue multiplexing, temporal analysis, change analysis, expression level analysis, and dose analysis. Such studies may allow researchers to investigate complex clinical conditions associated with several different proteins or biomarkers. For certain IHC studies of TMAs, the TMA slide is removed from the microscope after a round of staining and imaging, and bleached to remove the dye that is conjugated with the antibody. The tissue spots on the TMA may then be re-stained with the same dye (or other dyes) that may be conjugated with another antibody targeting different proteins, and the TMA is replaced under the microscope for imaging. This series of staining and bleaching steps on a single TMA may be repeated several times.
Because several images of the same TMA slide are generated from these studies, these images may be registered before further analysis is performed. A bottleneck in automated registration systems is the validation step, which includes the detection and correction of registration failures that may be the result of lost or folded tissue spots on the TMA. This is important because an undetected registration failure may lead to erroneous results in later stages of the automated analysis. In certain types of analysis, such as sequential multiplexing, tools to facilitate validation of the tissue quality in the TMA at each round of staining or bleaching may be advantageous. Tissue quality validation at each step helps to remove damaged tissue from subsequent analysis stages, thus avoiding inaccuracies in biomarker quantitation and tissue scoring. For example, if the registration is not successful for a given step, the protein expression measured at that step may not be correlated with measurement at any other step. Grossly folded or completely lost tissue cores may also influence the accuracy of results. In addition, a tissue core may be neither folded nor lost compared to the baseline state (initial state before any staining or bleaching), but the tissue core selected may have very few cells such that any quantitation will be misleading. Performing this validation for hundreds of tissue cores at each step of a sequentially multiplexed study is highly time-consuming.
Certain techniques for validation of individual tissue spots may involve visual inspection of the combined display of two or more images. For example, this may be accomplished by combining color channels, using two displays with paired cursors, or by using a checkerboard display. One disadvantage with this technique is the time that may be involved with reviewing images of each individual tissue spot. Other techniques provide analysis of an image-to-image metric value. However, this value is highly image-dependent and does not provide information about re-initialization of registration. Another technique involves an analysis of a resulting transformation. This technique is only useful if there is a ground truth to compare with, e.g., when registering to a synthetic image or an atlas. In another technique involving analysis of transformation stability, examining the Jacobian of the transform in the neighborhood of the transform returned by the registration method may be used. However, this approach does not preclude the selection of a local minimum, and does not suggest re-initialization values.